• DocumentCode
    2519261
  • Title

    Research on test paper auto-generating based on immune genetic algorithm

  • Author

    Yan-cong, Zhou ; Jun-hua, Gu ; Xiao-chen, Sun ; Yong-feng, Dong ; Ming, Fan

  • Author_Institution
    Tianjin Univ. of Commerce, Hebei Univ. of Technol., Tianjin, China
  • fYear
    2011
  • fDate
    23-25 May 2011
  • Firstpage
    2498
  • Lastpage
    2502
  • Abstract
    In order to improve the auto-generating test paper´s quality at the cost of low time, an intelligent algorithm based on immune genetic algorithm was proposed. In the algorithm immune process was added into the basic framework of genetic algorithm, and the algorithm based on vaccination was put forward and used for test paper auto-generating. The problem that genetic algorithm is precocity and easy to fall into a local optimization was resolved by this algorithm. The feasibility and validity of the algorithm was proved by test data compared with other algorithms. At last the validating system enhances the users´ condition constraints for test paper through manual inching, thus the system is more simple and practical.
  • Keywords
    educational administrative data processing; genetic algorithms; auto-generating test paper quality; immune genetic algorithm; intelligent algorithm; manual inching; Computers; Convergence; Databases; Genetic algorithms; Optimization; Testing; Vaccines; Genetic algorithm; Immune algorithm; Local convergence; Test paper auto-generating; Vaccination;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2011 Chinese
  • Conference_Location
    Mianyang
  • Print_ISBN
    978-1-4244-8737-0
  • Type

    conf

  • DOI
    10.1109/CCDC.2011.5968629
  • Filename
    5968629